Overview

Dataset statistics

Number of variables81
Number of observations7160
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 MiB
Average record size in memory648.0 B

Variable types

BOOL40
CAT25
NUM16

Warnings

aa2 is highly correlated with aaHigh correlation
aa is highly correlated with aa2High correlation
clearance is highly correlated with clearancecockHigh correlation
clearancecock is highly correlated with clearanceHigh correlation
surg is highly correlated with procedureHigh correlation
procedure is highly correlated with surgHigh correlation
number has 6470 (90.4%) zeros Zeros
angorclasseccs has 5387 (75.2%) zeros Zeros

Reproduction

Analysis started2020-11-30 21:06:05.102758
Analysis finished2020-11-30 21:07:54.577478
Duration1 minute and 49.47 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

es1
Real number (ℝ≥0)

Distinct1971
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.357738991
Minimum0.8810525718
Maximum88.48248395
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:07:54.743382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.8810525718
5-th percentile1.005392068
Q12.08257992
median4.446640765
Q38.627906637
95-th percentile23.85991488
Maximum88.48248395
Range87.60143138
Interquartile range (IQR)6.545326718

Descriptive statistics

Standard deviation9.430859073
Coefficient of variation (CV)1.281760482
Kurtosis18.92366034
Mean7.357738991
Median Absolute Deviation (MAD)2.711523602
Skewness3.733432062
Sum52681.41118
Variance88.94110285
MonotocityNot monotonic
2020-11-30T18:07:54.952263image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1.5054309613575.0%
 
0.88105257182924.1%
 
2.082579922703.8%
 
4.6480136841692.4%
 
1.5113518191371.9%
 
1.333689624761.1%
 
5.479038476711.0%
 
3.999065565670.9%
 
6.352257865530.7%
 
1.683913851510.7%
 
Other values (1961)561778.4%
 
ValueCountFrequency (%) 
0.88105257182924.1%
 
0.9411907096410.6%
 
1.005392068310.4%
 
1.073925311340.5%
 
1.147076038270.4%
 
ValueCountFrequency (%) 
88.482483951< 0.1%
 
86.373478941< 0.1%
 
85.882127531< 0.1%
 
84.879804621< 0.1%
 
84.471651451< 0.1%
 

es2
Real number (ℝ≥0)

Distinct4802
Distinct (%)67.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.172159395
Minimum0.49865156
Maximum94.42075474
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:07:55.245096image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0.49865156
5-th percentile0.6691633775
Q11.212628256
median2.432048073
Q35.054356684
95-th percentile18.17426679
Maximum94.42075474
Range93.92210318
Interquartile range (IQR)3.841728428

Descriptive statistics

Standard deviation9.079529069
Coefficient of variation (CV)1.75546196
Kurtosis28.79470349
Mean5.172159395
Median Absolute Deviation (MAD)1.481102758
Skewness4.832278421
Sum37032.66127
Variance82.43784811
MonotocityNot monotonic
2020-11-30T18:07:55.551918image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0.49865156941.3%
 
0.6733049492731.0%
 
0.6691633775490.7%
 
0.8041374276470.7%
 
0.580551453400.6%
 
0.6820668878340.5%
 
0.6743124659340.5%
 
2.755068384310.4%
 
0.5546841114300.4%
 
3.308568087300.4%
 
Other values (4792)669893.5%
 
ValueCountFrequency (%) 
0.49865156941.3%
 
0.501743134380.1%
 
0.513002866390.1%
 
0.527765015880.1%
 
0.53103612641< 0.1%
 
ValueCountFrequency (%) 
94.420754741< 0.1%
 
91.697916111< 0.1%
 
89.310710881< 0.1%
 
85.785110711< 0.1%
 
85.62182521< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
4869 
1
2291 
ValueCountFrequency (%) 
0486968.0%
 
1229132.0%
 
2020-11-30T18:07:55.743808image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

agepat
Real number (ℝ≥0)

Distinct77
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.65726257
Minimum18
Maximum94
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:07:55.883730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile37
Q155
median65
Q375
95-th percentile83
Maximum94
Range76
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.11531798
Coefficient of variation (CV)0.2217393179
Kurtosis0.1595236355
Mean63.65726257
Median Absolute Deviation (MAD)10
Skewness-0.6632493769
Sum455786
Variance199.2422018
MonotocityNot monotonic
2020-11-30T18:07:56.162568image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
622203.1%
 
752203.1%
 
682153.0%
 
662092.9%
 
702062.9%
 
762022.8%
 
672022.8%
 
742022.8%
 
652002.8%
 
611982.8%
 
Other values (67)508671.0%
 
ValueCountFrequency (%) 
1870.1%
 
1980.1%
 
2090.1%
 
2190.1%
 
22180.3%
 
ValueCountFrequency (%) 
941< 0.1%
 
931< 0.1%
 
921< 0.1%
 
9170.1%
 
90110.2%
 

smoker
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
3480 
past
2534 
current
1116 
unknown
 
30
ValueCountFrequency (%) 
no348048.6%
 
past253435.4%
 
current111615.6%
 
unknown300.4%
 
2020-11-30T18:07:56.658338image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:07:57.184058image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:57.495880image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length4
Mean length3.508100559
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
yes
4024 
no
3136 
ValueCountFrequency (%) 
yes402456.2%
 
no313643.8%
 
2020-11-30T18:07:57.748736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

diabetes__status
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
5348 
oral_therapy
1247 
insulin
565 
ValueCountFrequency (%) 
no534874.7%
 
oral_therapy124717.4%
 
insulin5657.9%
 
2020-11-30T18:07:58.053560image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:07:58.243450image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:58.471322image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length2
Mean length4.136173184
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
yes
3591 
no
3569 
ValueCountFrequency (%) 
yes359150.2%
 
no356949.8%
 
2020-11-30T18:07:58.622234image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
4424 
stable_angina
1279 
non_stemi
735 
stemi
722 
ValueCountFrequency (%) 
no442461.8%
 
stable_angina127917.9%
 
non_stemi73510.3%
 
stemi72210.1%
 
2020-11-30T18:07:58.780145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:07:58.985025image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:59.218891image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length4.98603352
Min length2

acs_different_
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
_less_than__7_d
6081 
_less_than__90_d
 
605
_larger_than__90_d
 
474
ValueCountFrequency (%) 
_less_than__7_d608184.9%
 
_less_than__90_d6058.4%
 
_larger_than__90_d4746.6%
 
2020-11-30T18:07:59.393791image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:07:59.520738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:59.669632image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length18
Median length15
Mean length15.28310056
Min length15
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6297 
yes
863 
ValueCountFrequency (%) 
no629787.9%
 
yes86312.1%
 
2020-11-30T18:07:59.801580image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

recentmi_a
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6166 
1
994 
ValueCountFrequency (%) 
0616686.1%
 
199413.9%
 
2020-11-30T18:07:59.860523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6435 
valvular
 
574
cabg
 
68
others
 
53
combined
 
30
ValueCountFrequency (%) 
no643589.9%
 
valvular5748.0%
 
cabg680.9%
 
others530.7%
 
combined300.4%
 
2020-11-30T18:07:59.981474image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:00.128371image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:00.315262image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length8
Median length2
Mean length2.554748603
Min length2

number
Real number (ℝ≥0)

ZEROS

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1272524071
Minimum0
Maximum5
Zeros6470
Zeros (%)90.4%
Memory size55.9 KiB
2020-11-30T18:08:00.481168image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum5
Range5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4350660287
Coefficient of variation (CV)3.418921801
Kurtosis21.32680693
Mean0.1272524071
Median Absolute Deviation (MAD)0
Skewness4.195820158
Sum911.1272346
Variance0.1892824493
MonotocityNot monotonic
2020-11-30T18:08:00.655070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%) 
0647090.4%
 
15167.2%
 
21311.8%
 
3370.5%
 
43< 0.1%
 
52< 0.1%
 
0.12723463691< 0.1%
 
ValueCountFrequency (%) 
0647090.4%
 
0.12723463691< 0.1%
 
15167.2%
 
21311.8%
 
3370.5%
 
ValueCountFrequency (%) 
52< 0.1%
 
43< 0.1%
 
3370.5%
 
21311.8%
 
15167.2%
 
Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6178 
carotid__larger_than_50_percent_
 
381
lower_limbs
 
337
previous_vascular_surgery
 
264
ValueCountFrequency (%) 
no617886.3%
 
carotid__larger_than_50_percent_3815.3%
 
lower_limbs3374.7%
 
previous_vascular_surgery2643.7%
 
2020-11-30T18:08:00.831966image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:00.951899image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:01.561550image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length2
Mean length4.86801676
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6178 
1
982 
ValueCountFrequency (%) 
0617886.3%
 
198213.7%
 
2020-11-30T18:08:02.136220image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6034 
yes
1126 
ValueCountFrequency (%) 
no603484.3%
 
yes112615.7%
 
2020-11-30T18:08:02.401067image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6936 
yes
 
224
ValueCountFrequency (%) 
no693696.9%
 
yes2243.1%
 
2020-11-30T18:08:02.522002image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6738 
stroke
 
259
peripheral
 
101
visceral
 
47
thrombosis
 
15
ValueCountFrequency (%) 
no673894.1%
 
stroke2593.6%
 
peripheral1011.4%
 
visceral470.7%
 
thrombosis150.2%
 
2020-11-30T18:08:03.058694image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:03.725310image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:04.245011image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length2
Mean length2.313687151
Min length2

previous_stroke
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6558 
ischemic_stroke
 
341
tia
 
199
hemorragic_stroke
 
62
ValueCountFrequency (%) 
no655891.6%
 
ischemic_stroke3414.8%
 
tia1992.8%
 
hemorragic_stroke620.9%
 
2020-11-30T18:08:04.934830image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:05.162700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:05.379575image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length2
Mean length2.776815642
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6948 
yes
 
212
ValueCountFrequency (%) 
no694897.0%
 
yes2123.0%
 
2020-11-30T18:08:05.513500image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6948 
1
 
212
ValueCountFrequency (%) 
0694897.0%
 
12123.0%
 
2020-11-30T18:08:05.580472image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

copd
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6466 
yes_treated
 
412
untreaded
 
282
ValueCountFrequency (%) 
no646690.3%
 
yes_treated4125.8%
 
untreaded2823.9%
 
2020-11-30T18:08:05.704389image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:05.917267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:06.207106image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length11
Median length2
Mean length2.793575419
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6748 
1
 
412
ValueCountFrequency (%) 
0674894.2%
 
14125.8%
 
2020-11-30T18:08:06.323042image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

ulcer
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6851 
yes
 
309
ValueCountFrequency (%) 
no685195.7%
 
yes3094.3%
 
2020-11-30T18:08:06.389004image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

neoplasia
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6595 
_less_than_5years
 
469
no_metatstasis
 
76
metatstasis
 
20
ValueCountFrequency (%) 
no659592.1%
 
_less_than_5years4696.6%
 
no_metatstasis761.1%
 
metatstasis200.3%
 
2020-11-30T18:08:06.547911image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:06.667841image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:06.832748image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length2
Mean length3.135055866
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
7024 
yes
 
136
ValueCountFrequency (%) 
no702498.1%
 
yes1361.9%
 
2020-11-30T18:08:06.948700image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

cirrhosis
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
7085 
uncomplicated
 
45
pht
 
30
ValueCountFrequency (%) 
no708599.0%
 
uncomplicated450.6%
 
pht300.4%
 
2020-11-30T18:08:07.073610image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:07.209530image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:07.334458image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length2.073324022
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
7089 
yes
 
71
ValueCountFrequency (%) 
no708999.0%
 
yes711.0%
 
2020-11-30T18:08:07.448413image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

weight
Real number (ℝ≥0)

Distinct104
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean75.41323834
Minimum32
Maximum157
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:07.606302image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum32
5-th percentile52
Q165
median75
Q385
95-th percentile101
Maximum157
Range125
Interquartile range (IQR)20

Descriptive statistics

Standard deviation15.00789338
Coefficient of variation (CV)0.1990087379
Kurtosis0.5612346099
Mean75.41323834
Median Absolute Deviation (MAD)10
Skewness0.4647559722
Sum539958.7865
Variance225.2368638
MonotocityNot monotonic
2020-11-30T18:08:08.658699image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
704005.6%
 
803955.5%
 
753054.3%
 
602363.3%
 
652343.3%
 
852112.9%
 
782022.8%
 
901942.7%
 
721942.7%
 
681872.6%
 
Other values (94)460264.3%
 
ValueCountFrequency (%) 
321< 0.1%
 
341< 0.1%
 
352< 0.1%
 
362< 0.1%
 
372< 0.1%
 
ValueCountFrequency (%) 
1571< 0.1%
 
1551< 0.1%
 
1402< 0.1%
 
1362< 0.1%
 
1332< 0.1%
 

height
Real number (ℝ≥0)

Distinct66
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.4405544
Minimum135
Maximum205
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:08.905557image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile153
Q1162
median169
Q3175
95-th percentile183
Maximum205
Range70
Interquartile range (IQR)13

Descriptive statistics

Standard deviation9.442042055
Coefficient of variation (CV)0.05605563393
Kurtosis0.04720404379
Mean168.4405544
Median Absolute Deviation (MAD)6
Skewness-0.001923729444
Sum1206034.369
Variance89.15215818
MonotocityNot monotonic
2020-11-30T18:08:09.127451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
1706348.9%
 
1604626.5%
 
1654496.3%
 
1753855.4%
 
1803474.8%
 
1723124.4%
 
1682834.0%
 
1732693.8%
 
1762313.2%
 
1692263.2%
 
Other values (56)356249.7%
 
ValueCountFrequency (%) 
1352< 0.1%
 
140120.2%
 
14140.1%
 
14260.1%
 
1432< 0.1%
 
ValueCountFrequency (%) 
20540.1%
 
2041< 0.1%
 
2021< 0.1%
 
2002< 0.1%
 
1993< 0.1%
 

bmi
Real number (ℝ≥0)

Distinct1934
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.52469675
Minimum11.97954711
Maximum50.21913806
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:09.432257image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum11.97954711
5-th percentile19.81361719
Q123.45679012
median26.02461194
Q329.06879615
95-th percentile34.79803646
Maximum50.21913806
Range38.23959094
Interquartile range (IQR)5.612006027

Descriptive statistics

Standard deviation4.60888587
Coefficient of variation (CV)0.173758287
Kurtosis1.195529988
Mean26.52469675
Median Absolute Deviation (MAD)2.799180093
Skewness0.7142305474
Sum189916.8287
Variance21.24182897
MonotocityNot monotonic
2020-11-30T18:08:10.029056image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
24.22145329550.8%
 
25.95155709470.7%
 
27.6816609460.6%
 
23.4375400.6%
 
24.69135802350.5%
 
25.71166208350.5%
 
27.34375340.5%
 
24.48979592330.5%
 
27.54820937290.4%
 
26.12244898280.4%
 
Other values (1924)677894.7%
 
ValueCountFrequency (%) 
11.979547111< 0.1%
 
13.427202791< 0.1%
 
13.590449951< 0.1%
 
14.429606161< 0.1%
 
14.605054971< 0.1%
 
ValueCountFrequency (%) 
50.219138061< 0.1%
 
49.60317461< 0.1%
 
48.487836951< 0.1%
 
48.456790121< 0.1%
 
47.839506171< 0.1%
 

cardiac_rhythm
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
sinusal
6310 
fa_ou_tsv
850 
ValueCountFrequency (%) 
sinusal631088.1%
 
fa_ou_tsv85011.9%
 
2020-11-30T18:08:10.625101image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:11.077842image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:11.579637image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length9
Median length7
Mean length7.237430168
Min length7

nyhaclass
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
3
2789 
4
2161 
1
1538 
2
672 
ValueCountFrequency (%) 
3278939.0%
 
4216130.2%
 
1153821.5%
 
26729.4%
 
2020-11-30T18:08:12.482121image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:12.643028image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:12.822927image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

angorclasseccs
Real number (ℝ≥0)

ZEROS

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5675977654
Minimum0
Maximum4
Zeros5387
Zeros (%)75.2%
Memory size55.9 KiB
2020-11-30T18:08:13.028806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum4
Range4
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.051361716
Coefficient of variation (CV)1.852300662
Kurtosis1.065523578
Mean0.5675977654
Median Absolute Deviation (MAD)0
Skewness1.56780124
Sum4064
Variance1.105361459
MonotocityNot monotonic
2020-11-30T18:08:13.270668image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)
ValueCountFrequency (%) 
0538775.2%
 
2100214.0%
 
35027.0%
 
11742.4%
 
4951.3%
 
ValueCountFrequency (%) 
0538775.2%
 
11742.4%
 
2100214.0%
 
35027.0%
 
4951.3%
 
ValueCountFrequency (%) 
4951.3%
 
35027.0%
 
2100214.0%
 
11742.4%
 
0538775.2%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6781 
yes
 
379
ValueCountFrequency (%) 
no678194.7%
 
yes3795.3%
 
2020-11-30T18:08:13.508531image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6839 
yes
 
321
ValueCountFrequency (%) 
no683995.5%
 
yes3214.5%
 
2020-11-30T18:08:13.592483image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6839 
1
 
321
ValueCountFrequency (%) 
0683995.5%
 
13214.5%
 
2020-11-30T18:08:13.709418image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6942 
1
 
218
ValueCountFrequency (%) 
0694297.0%
 
12183.0%
 
2020-11-30T18:08:13.794368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

creatinine
Real number (ℝ≥0)

Distinct319
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean100.8511706
Minimum35
Maximum999
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:14.041226image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum35
5-th percentile59
Q175
median88
Q3106
95-th percentile167
Maximum999
Range964
Interquartile range (IQR)31

Descriptive statistics

Standard deviation65.60877409
Coefficient of variation (CV)0.6505504466
Kurtosis70.10723991
Mean100.8511706
Median Absolute Deviation (MAD)15
Skewness7.145745288
Sum722094.3817
Variance4304.511238
MonotocityNot monotonic
2020-11-30T18:08:14.312071image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
851502.1%
 
761492.1%
 
881492.1%
 
801472.1%
 
751442.0%
 
771422.0%
 
821381.9%
 
891371.9%
 
861361.9%
 
781351.9%
 
Other values (309)573380.1%
 
ValueCountFrequency (%) 
3540.1%
 
372< 0.1%
 
381< 0.1%
 
392< 0.1%
 
401< 0.1%
 
ValueCountFrequency (%) 
99940.1%
 
9981< 0.1%
 
9901< 0.1%
 
9521< 0.1%
 
9491< 0.1%
 

clearancecock
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1432
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.1890056
Minimum4.8
Maximum262.4
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:14.517972image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum4.8
5-th percentile31.195
Q154.6
median74.15
Q395.8
95-th percentile134.6
Maximum262.4
Range257.6
Interquartile range (IQR)41.2

Descriptive statistics

Standard deviation32.12278539
Coefficient of variation (CV)0.4161575232
Kurtosis1.202322134
Mean77.1890056
Median Absolute Deviation (MAD)20.55
Skewness0.7261806962
Sum552673.2801
Variance1031.873341
MonotocityNot monotonic
2020-11-30T18:08:14.738846image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
77.18650749831.2%
 
88.5200.3%
 
72.1190.3%
 
73.4180.3%
 
64.3170.2%
 
47170.2%
 
98.3160.2%
 
76.9160.2%
 
56.4160.2%
 
57160.2%
 
Other values (1422)692296.7%
 
ValueCountFrequency (%) 
4.81< 0.1%
 
5.61< 0.1%
 
5.93< 0.1%
 
6.11< 0.1%
 
6.82< 0.1%
 
ValueCountFrequency (%) 
262.41< 0.1%
 
259.51< 0.1%
 
248.21< 0.1%
 
247.51< 0.1%
 
238.81< 0.1%
 

lvef
Real number (ℝ≥0)

Distinct73
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean57.82437087
Minimum10
Maximum89
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:14.970693image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile35
Q150
median60
Q366
95-th percentile75
Maximum89
Range79
Interquartile range (IQR)16

Descriptive statistics

Standard deviation11.97766587
Coefficient of variation (CV)0.2071387148
Kurtosis0.4715618029
Mean57.82437087
Median Absolute Deviation (MAD)7
Skewness-0.6577950151
Sum414022.4954
Variance143.4644796
MonotocityNot monotonic
2020-11-30T18:08:15.316496image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
60144220.1%
 
557019.8%
 
706569.2%
 
506318.8%
 
654406.1%
 
453474.8%
 
402413.4%
 
351682.3%
 
301532.1%
 
681161.6%
 
Other values (63)226531.6%
 
ValueCountFrequency (%) 
101< 0.1%
 
152< 0.1%
 
161< 0.1%
 
171< 0.1%
 
20410.6%
 
ValueCountFrequency (%) 
892< 0.1%
 
883< 0.1%
 
872< 0.1%
 
8650.1%
 
8560.1%
 

papsyst
Real number (ℝ≥0)

Distinct79
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.26595446
Minimum10
Maximum125
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:15.548382image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile26
Q140
median42.26595446
Q342.26595446
95-th percentile60
Maximum125
Range115
Interquartile range (IQR)2.265954456

Descriptive statistics

Standard deviation10.06598156
Coefficient of variation (CV)0.2381581509
Kurtosis6.712298828
Mean42.26595446
Median Absolute Deviation (MAD)0
Skewness1.598280518
Sum302624.2339
Variance101.3239848
MonotocityNot monotonic
2020-11-30T18:08:15.872177image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
42.26595446360350.3%
 
303605.0%
 
403544.9%
 
353164.4%
 
452813.9%
 
502723.8%
 
252293.2%
 
551442.0%
 
601422.0%
 
70781.1%
 
Other values (69)138119.3%
 
ValueCountFrequency (%) 
101< 0.1%
 
121< 0.1%
 
141< 0.1%
 
1550.1%
 
162< 0.1%
 
ValueCountFrequency (%) 
1251< 0.1%
 
1201< 0.1%
 
1131< 0.1%
 
1102< 0.1%
 
1052< 0.1%
 

lvefisotopic
Real number (ℝ≥0)

Distinct73
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55.26565144
Minimum14
Maximum91
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:16.167007image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile55.26565144
Q155.26565144
median55.26565144
Q355.26565144
95-th percentile55.26565144
Maximum91
Range77
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.393408514
Coefficient of variation (CV)0.07949618615
Kurtosis28.66663966
Mean55.26565144
Median Absolute Deviation (MAD)0
Skewness-1.399613373
Sum395702.0643
Variance19.30203837
MonotocityNot monotonic
2020-11-30T18:08:16.399881image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
55.26565144656991.7%
 
60320.4%
 
55310.4%
 
65270.4%
 
50270.4%
 
70190.3%
 
64190.3%
 
40190.3%
 
69160.2%
 
45150.2%
 
Other values (63)3865.4%
 
ValueCountFrequency (%) 
141< 0.1%
 
152< 0.1%
 
181< 0.1%
 
192< 0.1%
 
202< 0.1%
 
ValueCountFrequency (%) 
911< 0.1%
 
871< 0.1%
 
853< 0.1%
 
841< 0.1%
 
831< 0.1%
 
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
3632 
yes
3528 
ValueCountFrequency (%) 
no363250.7%
 
yes352849.3%
 
2020-11-30T18:08:16.635739image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
yes
4124 
no
3036 
ValueCountFrequency (%) 
yes412457.6%
 
no303642.4%
 
2020-11-30T18:08:16.694707image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
3673 
ao_stenosis
1743 
org_mr
794 
aoi
514 
mitral_stenosis
 
361
Other values (2)
 
75
ValueCountFrequency (%) 
no367351.3%
 
ao_stenosis174324.3%
 
org_mr79411.1%
 
aoi5147.2%
 
mitral_stenosis3615.0%
 
fctl_mr470.7%
 
tricuspid280.4%
 
2020-11-30T18:08:16.829629image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:16.961554image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:17.144451image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length2
Mean length5.421927374
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6643 
yes
 
517
ValueCountFrequency (%) 
no664392.8%
 
yes5177.2%
 
2020-11-30T18:08:17.266379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

tricuspid
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6434 
yes
726 
ValueCountFrequency (%) 
no643489.9%
 
yes72610.1%
 
2020-11-30T18:08:17.324343image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

etiology
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
3548 
degenerative_or_dystrophic
2145 
rheumatic
660 
endocarditis
363 
congenital
 
252
Other values (2)
 
192
ValueCountFrequency (%) 
no354849.6%
 
degenerative_or_dystrophic214530.0%
 
rheumatic6609.2%
 
endocarditis3635.1%
 
congenital2523.5%
 
others1832.6%
 
inflammatory90.1%
 
2020-11-30T18:08:17.538222image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:17.672145image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:18.056926image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length26
Median length6
Mean length10.73854749
Min length2

redo_a
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6602 
autre
 
162
mitral_valve_repair_failure
 
123
bioproth_dot__failure
 
112
endocarditis
 
75
Other values (3)
 
86
ValueCountFrequency (%) 
no660292.2%
 
autre1622.3%
 
mitral_valve_repair_failure1231.7%
 
bioproth_dot__failure1121.6%
 
endocarditis751.0%
 
prosthetic_valve_thrombosis520.7%
 
cabg280.4%
 
yes60.1%
 
2020-11-30T18:08:18.597614image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:18.765517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:18.953414image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length27
Median length2
Mean length3.08952514
Min length2

ascendingaorta
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6563 
aneurysm
 
447
dissection
 
150
ValueCountFrequency (%) 
no656391.7%
 
aneurysm4476.2%
 
dissection1502.1%
 
2020-11-30T18:08:19.129309image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:19.248242image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:19.400156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length2
Mean length2.542178771
Min length2
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
7070 
yes
 
90
ValueCountFrequency (%) 
no707098.7%
 
yes901.3%
 
2020-11-30T18:08:19.521107image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

others
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6989 
others
 
85
tumor
 
62
pericarditis
 
18
dissection_type_b
 
4
Other values (2)
 
2
ValueCountFrequency (%) 
no698997.6%
 
others851.2%
 
tumor620.9%
 
pericarditis180.3%
 
dissection_type_b40.1%
 
dissection1< 0.1%
 
transplantation1< 0.1%
 
2020-11-30T18:08:19.656009image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2020-11-30T18:08:19.783933image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:19.964850image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length17
Median length2
Mean length2.109916201
Min length2

urgency
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6751 
yes
 
409
ValueCountFrequency (%) 
no675194.3%
 
yes4095.7%
 
2020-11-30T18:08:20.083783image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

urgency_a
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6751 
1
 
409
ValueCountFrequency (%) 
0675194.3%
 
14095.7%
 
2020-11-30T18:08:20.142730image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
yes
4134 
no
3026 
ValueCountFrequency (%) 
yes413457.7%
 
no302642.3%
 
2020-11-30T18:08:20.300640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

aortic
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
4400 
bioprosthesis
1728 
mechanical
997 
valve_repair
 
19
homograft
 
15
ValueCountFrequency (%) 
no440061.5%
 
bioprosthesis172824.1%
 
mechanical99713.9%
 
valve_repair190.3%
 
homograft150.2%
 
autogreffe1< 0.1%
 
2020-11-30T18:08:20.432562image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-30T18:08:20.544518image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:20.700428image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length5.81103352
Min length2

mitral
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
5464 
mechanical
662 
bioprosthesis
556 
valve_repair
 
478
ValueCountFrequency (%) 
no546476.3%
 
mechanical6629.2%
 
bioprosthesis5567.8%
 
valve_repair4786.7%
 
2020-11-30T18:08:20.884323image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:21.014230image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:21.163144image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length4.261452514
Min length2

triscupid
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6313 
valve_repair
766 
bioprosthesis
 
75
mechanical
 
3
homograft
 
3
ValueCountFrequency (%) 
no631388.2%
 
valve_repair76610.7%
 
bioprosthesis751.0%
 
mechanical3< 0.1%
 
homograft3< 0.1%
 
2020-11-30T18:08:21.367026image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:21.502949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:21.668873image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length13
Median length2
Mean length3.191340782
Min length2

cabg
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
3738 
yes
3422 
ValueCountFrequency (%) 
no373852.2%
 
yes342247.8%
 
2020-11-30T18:08:21.776813image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6459 
bentall_mec
 
210
ascending_aorta
 
156
ascending_plus_aortic__valve
 
102
ascending_aorta_plus_aortic_valve_repair
 
89
Other values (10)
 
144
ValueCountFrequency (%) 
no645990.2%
 
bentall_mec2102.9%
 
ascending_aorta1562.2%
 
ascending_plus_aortic__valve1021.4%
 
ascending_aorta_plus_aortic_valve_repair891.2%
 
bentall_bio741.0%
 
ascending_and_arch490.7%
 
bentall_bio_plus_pac50.1%
 
ascending_aorta_less_cabg50.1%
 
ascending_aorta_less_valve_repair50.1%
 
Other values (5)60.1%
 
2020-11-30T18:08:21.903738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)0.1%
2020-11-30T18:08:22.208544image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length40
Median length2
Mean length3.662988827
Min length2

others_dot_1
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
no
6822 
others
 
215
tumor
 
63
congenital
 
30
myomectomy
 
27
Other values (2)
 
3
ValueCountFrequency (%) 
no682295.3%
 
others2153.0%
 
tumor630.9%
 
congenital300.4%
 
myomectomy270.4%
 
pof2< 0.1%
 
af1< 0.1%
 
2020-11-30T18:08:22.431415image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2020-11-30T18:08:22.551368image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:22.734244image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length2
Mean length2.21047486
Min length2

weightofproc
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
isolated_cabg
2648 
single_non_cabg
2295 
2_procedures
1527 
3_procedures
690 
ValueCountFrequency (%) 
isolated_cabg264837.0%
 
single_non_cabg229532.1%
 
2_procedures152721.3%
 
3_procedures6909.6%
 
2020-11-30T18:08:23.317908image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:23.513816image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:23.652733image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length13
Mean length13.33142458
Min length12
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6754 
1
 
406
ValueCountFrequency (%) 
0675494.3%
 
14065.7%
 
2020-11-30T18:08:23.794634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

d30death
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6833 
1
 
327
ValueCountFrequency (%) 
0683395.4%
 
13274.6%
 
2020-11-30T18:08:23.851601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

aa
Real number (ℝ≥0)

HIGH CORRELATION

Distinct36
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.465782123
Minimum1
Maximum36
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:24.005517image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median7
Q317
95-th percentile25
Maximum36
Range35
Interquartile range (IQR)16

Descriptive statistics

Standard deviation8.628943721
Coefficient of variation (CV)0.9115933167
Kurtosis-0.849319264
Mean9.465782123
Median Absolute Deviation (MAD)6
Skewness0.6291229964
Sum67775
Variance74.45866973
MonotocityNot monotonic
2020-11-30T18:08:24.231385image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%) 
1246034.4%
 
42203.1%
 
172203.1%
 
102153.0%
 
82092.9%
 
122062.9%
 
182022.8%
 
92022.8%
 
162022.8%
 
72002.8%
 
Other values (26)282439.4%
 
ValueCountFrequency (%) 
1246034.4%
 
21782.5%
 
31982.8%
 
42203.1%
 
51862.6%
 
ValueCountFrequency (%) 
361< 0.1%
 
351< 0.1%
 
341< 0.1%
 
3370.1%
 
32110.2%
 

aa2
Real number (ℝ≥0)

HIGH CORRELATION

Distinct35
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.809357542
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:24.433288image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q316
95-th percentile24
Maximum35
Range34
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.298563172
Coefficient of variation (CV)0.9420168421
Kurtosis-0.7587018286
Mean8.809357542
Median Absolute Deviation (MAD)5
Skewness0.6976244753
Sum63075
Variance68.86615073
MonotocityNot monotonic
2020-11-30T18:08:24.616183image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%) 
1263836.8%
 
162203.1%
 
32203.1%
 
92153.0%
 
72092.9%
 
112062.9%
 
82022.8%
 
152022.8%
 
172022.8%
 
62002.8%
 
Other values (25)264637.0%
 
ValueCountFrequency (%) 
1263836.8%
 
21982.8%
 
32203.1%
 
41862.6%
 
51792.5%
 
ValueCountFrequency (%) 
351< 0.1%
 
341< 0.1%
 
331< 0.1%
 
3270.1%
 
31110.2%
 

redo
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6471 
1
689 
ValueCountFrequency (%) 
0647190.4%
 
16899.6%
 
2020-11-30T18:08:24.757102image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

mi
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
5703 
1
1457 
ValueCountFrequency (%) 
0570379.7%
 
1145720.3%
 
2020-11-30T18:08:24.814070image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

delaimi
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
1
6686 
0
 
474
ValueCountFrequency (%) 
1668693.4%
 
04746.6%
 
2020-11-30T18:08:24.872041image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6941 
1
 
219
ValueCountFrequency (%) 
0694196.9%
 
12193.1%
 
2020-11-30T18:08:24.927985image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

ua
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
7065 
1
 
95
ValueCountFrequency (%) 
0706598.7%
 
1951.3%
 
2020-11-30T18:08:24.989949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6827 
1
 
333
ValueCountFrequency (%) 
0682795.3%
 
13334.7%
 
2020-11-30T18:08:25.045917image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

lv1
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
7027 
1
 
133
ValueCountFrequency (%) 
0702798.1%
 
11331.9%
 
2020-11-30T18:08:25.105885image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

lv2
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6008 
1
1152 
ValueCountFrequency (%) 
0600883.9%
 
1115216.1%
 
2020-11-30T18:08:25.162852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6459 
1
701 
ValueCountFrequency (%) 
0645990.2%
 
17019.8%
 
2020-11-30T18:08:25.223815image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

procedure
Boolean

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
1
4512 
0
2648 
ValueCountFrequency (%) 
1451263.0%
 
0264837.0%
 
2020-11-30T18:08:25.287781image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
0
6595 
1
 
565
ValueCountFrequency (%) 
0659592.1%
 
15657.9%
 
2020-11-30T18:08:25.344745image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

clearance
Real number (ℝ≥0)

HIGH CORRELATION

Distinct6507
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77.18838315
Minimum5.551
Maximum262.728
Zeros0
Zeros (%)0.0%
Memory size55.9 KiB
2020-11-30T18:08:25.496679image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Quantile statistics

Minimum5.551
5-th percentile30.88606047
Q154.43321646
median73.90337954
Q396.06110039
95-th percentile134.8787852
Maximum262.728
Range257.177
Interquartile range (IQR)41.62788392

Descriptive statistics

Standard deviation32.28511673
Coefficient of variation (CV)0.4182639331
Kurtosis1.16818266
Mean77.18838315
Median Absolute Deviation (MAD)20.72208338
Skewness0.7246150068
Sum552668.8234
Variance1042.328762
MonotocityNot monotonic
2020-11-30T18:08:25.709556image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
77.18585061310.4%
 
92.25110.2%
 
88.56110.2%
 
108.24100.1%
 
103.3290.1%
 
98.480.1%
 
94.7180.1%
 
46.860.1%
 
102.0960.1%
 
110.760.1%
 
Other values (6497)705498.5%
 
ValueCountFrequency (%) 
5.5511< 0.1%
 
5.857555111< 0.1%
 
5.8585308061< 0.1%
 
5.9394594591< 0.1%
 
6.0603141361< 0.1%
 
ValueCountFrequency (%) 
262.7281< 0.1%
 
259.80612241< 0.1%
 
248.461< 0.1%
 
247.82222221< 0.1%
 
239.08857141< 0.1%
 

surg
Categorical

HIGH CORRELATION

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size55.9 KiB
1
4134 
0
2648 
2
 
378
ValueCountFrequency (%) 
1413457.7%
 
0264837.0%
 
23785.3%
 
2020-11-30T18:08:25.952398image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2020-11-30T18:08:26.098315image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:08:26.215266image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

Interactions

2020-11-30T18:06:40.677727image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:40.826619image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:40.971535image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:41.130444image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:41.312341image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:41.467251image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:41.617165image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:41.775077image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:41.939980image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:42.090914image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:42.239810image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:42.397738image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:42.548651image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:42.709541image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:42.866449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:43.025379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:43.177291image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:43.323207image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:43.470124image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:43.629032image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:43.788920image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:44.011792image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:44.175719image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:44.347604image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:44.521523image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:44.678412image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:44.948256image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:45.627865image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:45.826751image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:46.033634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:46.266501image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:46.445399image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:46.624317image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:46.788200image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:47.227949image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:47.658736image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:48.090018image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:48.611740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:48.826597image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:49.052469image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:49.244379image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:49.554180image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:50.134852image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:50.817267image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:51.436910image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:51.648790image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:51.856670image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:52.065549image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:52.664059image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:53.219744image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:53.588529image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:53.780634image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:53.949539image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:54.295342image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:54.853019image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:06:55.071895image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T18:07:23.158746image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T18:07:37.279355image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T18:07:37.629156image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T18:07:38.143859image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:38.318740image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:38.491640image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:38.711514image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:38.918396image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
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2020-11-30T18:07:39.259221image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:39.439097image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:39.606001image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:39.862858image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:40.069735image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:40.301601image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Correlations

2020-11-30T18:08:26.529066image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2020-11-30T18:08:28.129806image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2020-11-30T18:08:28.860364image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2020-11-30T18:08:29.750853image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2020-11-30T18:08:32.551449image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2020-11-30T18:07:41.151115image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/
2020-11-30T18:07:51.230354image/svg+xmlMatplotlib v3.3.2, https://matplotlib.org/

Sample

First rows

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Last rows

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